Graduate Program in Quantitative and Computational Biology, Baylor College of Medicine, United States.
Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, United States.
J Struct Biol. 2018 Nov;204(2):283-290. doi: 10.1016/j.jsb.2018.09.002. Epub 2018 Sep 4.
EMAN2 is an extensible software suite with complete workflows for performing high-resolution single particle analysis, 2-D and 3-D heterogeneity analysis, and subtomogram averaging, among other tasks. Participation in the recent CryoEM Map Challenge sponsored by the EMDatabank led to a number of significant improvements to the single particle analysis process in EMAN2. A new convolutional neural network particle picker was developed, which dramatically improves particle picking accuracy for difficult data sets. A new particle quality metric capable of accurately identifying "bad" particles with a high degree of accuracy, no human input, and a negligible amount of additional computation, has been introduced, and this now serves as a replacement for earlier human-biased methods. The way 3-D single particle reconstructions are filtered has been altered to be more comparable to the filter applied in several other popular software packages, dramatically improving the appearance of sidechains in high-resolution structures. Finally, an option has been added to perform local resolution-based iterative filtration, resulting in local resolution improvements in many maps.
EMAN2 是一个可扩展的软件套件，具有完整的工作流程，可用于执行高分辨率单颗粒分析、2D 和 3D 异质性分析以及子断层平均等任务。参与最近由 EMDatabank 赞助的 CryoEM Map Challenge，使得 EMAN2 中的单颗粒分析过程有了许多显著的改进。开发了一种新的卷积神经网络颗粒挑选器，极大地提高了困难数据集的颗粒挑选准确性。引入了一种新的颗粒质量指标，能够在无需人工输入和极少额外计算的情况下，高度准确地识别“不良”颗粒，现在它已替代了早期基于人工的方法。3D 单颗粒重建的滤波方式已被改变，以使其更类似于其他几个流行软件包应用的滤波器，极大地改善了高分辨率结构中侧链的外观。最后，添加了一个选项，可执行基于局部分辨率的迭代滤波，从而提高许多映射的局部分辨率。
